{"id":"https://openalex.org/W4312404745","doi":"https://doi.org/10.1109/tits.2022.3215613","title":"Spatial\u2013Temporal Tensor Graph Convolutional Network for Traffic Speed Prediction","display_name":"Spatial\u2013Temporal Tensor Graph Convolutional Network for Traffic Speed Prediction","publication_year":2022,"publication_date":"2022-11-04","ids":{"openalex":"https://openalex.org/W4312404745","doi":"https://doi.org/10.1109/tits.2022.3215613"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3215613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3215613","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007074176","display_name":"Xuran Xu","orcid":"https://orcid.org/0000-0003-4618-9163"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuran Xu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-4618-9163","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378754","display_name":"Tong Zhang","orcid":"https://orcid.org/0000-0001-6212-4891"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6212-4891","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054364063","display_name":"Chunyan Xu","orcid":"https://orcid.org/0000-0002-0814-4362"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyan Xu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-0814-4362","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025396815","display_name":"Zhen Cui","orcid":"https://orcid.org/0000-0002-0543-4196"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Cui","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-0543-4196","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100726984","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0003-4800-832X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-4800-832X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":2.8876,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.90841495,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"24","issue":"1","first_page":"92","last_page":"103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6775450706481934},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5953172445297241},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5750311017036438},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5543960332870483},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.5025408267974854},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.42093801498413086},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4118267893791199},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37281447649002075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34137919545173645},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25245368480682373}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6775450706481934},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5953172445297241},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5750311017036438},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5543960332870483},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.5025408267974854},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42093801498413086},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4118267893791199},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37281447649002075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34137919545173645},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25245368480682373},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3215613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3215613","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6499999761581421}],"awards":[{"id":"https://openalex.org/G1065978008","display_name":"\u56fe\u5efa\u6a21\u5b66\u4e60\u53ca\u5176\u89c6\u89c9\u5e94\u7528\u7814\u7a76","funder_award_id":"62072244","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4073614178","display_name":null,"funder_award_id":"ZR2020LZH008","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G61836106","display_name":null,"funder_award_id":"61906094","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W570916743","https://openalex.org/W1501565421","https://openalex.org/W1502922572","https://openalex.org/W1512018163","https://openalex.org/W1963826206","https://openalex.org/W1964357740","https://openalex.org/W1980518068","https://openalex.org/W1986326495","https://openalex.org/W1986678274","https://openalex.org/W1994377164","https://openalex.org/W2002033255","https://openalex.org/W2004353783","https://openalex.org/W2018282388","https://openalex.org/W2024165284","https://openalex.org/W2025603201","https://openalex.org/W2036718271","https://openalex.org/W2057482568","https://openalex.org/W2070802230","https://openalex.org/W2129660037","https://openalex.org/W2138860952","https://openalex.org/W2163517193","https://openalex.org/W2414050446","https://openalex.org/W2469230926","https://openalex.org/W2565330852","https://openalex.org/W2798918712","https://openalex.org/W2807894308","https://openalex.org/W2901504064","https://openalex.org/W2903871660","https://openalex.org/W2963588627","https://openalex.org/W2998313947","https://openalex.org/W3003862857","https://openalex.org/W3080344546","https://openalex.org/W3110353846","https://openalex.org/W3179429918","https://openalex.org/W4230512065","https://openalex.org/W6637178625","https://openalex.org/W6713582119","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6730235577","https://openalex.org/W6746015598","https://openalex.org/W6769934737","https://openalex.org/W6778398424","https://openalex.org/W6785773631"],"related_works":["https://openalex.org/W4379256054","https://openalex.org/W2093953080","https://openalex.org/W2911706637","https://openalex.org/W47805180","https://openalex.org/W3216281372","https://openalex.org/W2963838862","https://openalex.org/W2608089480","https://openalex.org/W3015641590","https://openalex.org/W2987657992","https://openalex.org/W4297666106"],"abstract_inverted_index":{"Accurate":[0],"traffic":[1,45,123],"speed":[2,46],"prediction":[3,152],"is":[4,147],"crucial":[5],"for":[6,44],"the":[7,16,101,131,139],"guidance":[8],"and":[9,27,52,61,72,93,112,154],"management":[10],"of":[11,122,133],"urban":[12],"traffic,":[13],"which":[14,104],"at":[15],"same":[17],"time":[18],"requires":[19],"a":[20,23,37,55,74,95],"model":[21],"with":[22],"satisfactory":[24],"computational":[25,102],"burden":[26],"memory":[28],"space":[29,71],"in":[30,108,130],"applications.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35,116],"propose":[36,73],"factorized":[38,96],"Spatial-Temporal":[39],"Tensor":[40],"Graph":[41],"Convolutional":[42],"Network":[43],"prediction.":[47],"Traffic":[48],"networks":[49],"are":[50],"modeled":[51],"unified":[53],"into":[54,69],"graph":[56,67,76,86],"tensor":[57,70,75,97,134],"that":[58,144],"integrates":[59],"spatial":[60],"temporal":[62],"information":[63],"simultaneously.":[64],"We":[65,88],"extend":[66],"convolution":[68,77,98],"network":[78],"to":[79,99],"extract":[80],"more":[81,148],"discriminating":[82],"features":[83],"from":[84,119],"spatial-temporal":[85],"data.":[87],"further":[89],"introduce":[90],"Tucker":[91],"decomposition":[92],"derive":[94],"reduce":[100],"burden,":[103],"performs":[105],"separate":[106],"filtering":[107],"small-scale":[109],"space,":[110],"time,":[111],"feature":[113],"modes.":[114],"Besides,":[115],"can":[117],"benefit":[118],"noise":[120],"suppression":[121],"data":[124],"when":[125],"discarding":[126],"those":[127],"trivial":[128],"components":[129],"process":[132],"decomposition.":[135],"Extensive":[136],"experiments":[137],"on":[138],"three":[140],"real-world":[141],"datasets":[142],"demonstrate":[143],"our":[145],"method":[146],"effective":[149],"than":[150],"traditional":[151],"methods,":[153],"achieves":[155],"state-of-the-art":[156],"performance.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
